Author

Ingrid Hobæk Haff

University of Oslo

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:CITE-seq· 1 Approach:machine learning (classical)· 1 Approach:simulation· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Andrei SlabodkiniD· 2 shared Chakravarthi KanduriiD· 2 shared Geir Kjetil SandveiD· 2 shared Gur YaariiD· 2 shared Lonneke SchefferiD· 2 shared Maria ChernigovskayaiD· 2 shared Milena PavlovićiD· 2 shared Philippe Auguste RobertiD· 2 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Andrei SlabodkinORCID

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2 papers

Recent·Most cited

BioinformaticsNucleic Acids ResearchPeer-reviewedJan 24, 2025

Simulation of adaptive immune receptors and repertoires with complex immune information to guide the development and benchmarking of AIRR machine learning

Maria Chernigovskaya, Milena Pavlović, Chakravarthi Kanduri…·Victor Greiff

This paper introduces LIgO, a software suite that simulates adaptive immune receptor repertoires with immune information to aid in developing and benchmarking AIRR machine learning methods.

17 citations

CITE-seqsimulation

𝕏 PostBluesky

BioinformaticsNature Machine IntelligencePeer-reviewedNov 16, 2021

immuneML: an ecosystem for machine learning analysis of adaptive immune receptor repertoires

Milena Pavlović, Lonneke Scheffer, Keshav Motwani…·Geir Kjetil Sandve

immuneML provides an open-source ecosystem for reproducible and interoperable machine learning analysis of adaptive immune receptor repertoires, demonstrating its utility through benchmarking and novel methods.

87 citationstop 3%

machine learning (classical)benchmarking

𝕏 PostBluesky